Research Data Policy

Research Data Policy

The Journal of Artificial Intelligence and Human Sciences (YZIB) is committed to promoting transparency, reproducibility, research integrity, and the responsible management of research data.

YZIB encourages authors to make the data, code, materials, protocols, and other research outputs underlying their published findings available whenever this is ethically, legally, and practically possible.

The journal recognizes that data-sharing practices differ across disciplines and that some research data cannot be made publicly available because of ethical, legal, privacy, confidentiality, intellectual property, contractual, security, or third-party restrictions.

1. Definition of Research Data

For the purposes of this policy, research data may include, but are not limited to:

  • raw and processed datasets;

  • survey and experimental data;

  • qualitative research data;

  • interview and observational data;

  • statistical analysis files;

  • software and source code;

  • algorithms and computational models;

  • machine-learning datasets;

  • model configurations and relevant parameters;

  • research protocols and methodological materials;

  • questionnaires, scales, and instruments;

  • supplementary materials;

  • images, audio, or video files generated during research; and

  • other materials necessary to understand, validate, or reproduce the findings of a study.

The nature of relevant research data may vary according to the discipline, methodology, and research design.

2. Data Sharing

Authors are encouraged to share research data supporting the findings of their articles whenever sharing is ethically and legally permissible.

Research data should preferably be deposited in:

  • recognized discipline-specific repositories;

  • institutional repositories;

  • general-purpose research data repositories; or

  • other reliable repositories that provide long-term preservation and stable access.

Where possible, authors should select repositories that provide a persistent identifier, such as a Digital Object Identifier (DOI), and appropriate metadata.

YZIB encourages authors to follow the FAIR Data Principles, according to which research data should, where appropriate, be Findable, Accessible, Interoperable, and Reusable.

3. Data Availability Statement

Original research articles that generate or analyze research data should include a Data Availability Statement.

The statement should indicate:

  • whether the data supporting the findings are publicly available;

  • where the data can be accessed;

  • the repository name and persistent identifier or link, where applicable;

  • whether the data are available from the corresponding author upon reasonable request; or

  • why the data cannot be made publicly available.

Examples of acceptable statements include:

Publicly available data

The data supporting the findings of this study are available in [repository name] at [DOI or persistent link].

Data available upon reasonable request

The data supporting the findings of this study are available from the corresponding author upon reasonable request.

Restricted data

The data supporting the findings of this study are not publicly available due to ethical, privacy, confidentiality, legal, or institutional restrictions.

Third-party data

The data used in this study were obtained from a third party and are subject to access restrictions. Requests for access should be directed to [relevant source or organization], where applicable.

No new data

No new data were created or analyzed in this study. Data sharing is therefore not applicable to this article.

Authors should select or adapt the statement that accurately reflects the circumstances of their research.

4. Sensitive, Personal, and Confidential Data

The protection of research participants, personal data, confidential information, and legally protected information takes precedence over open-data considerations.

Authors must not publicly disclose data that could:

  • identify research participants without appropriate consent;

  • violate privacy or data-protection requirements;

  • breach confidentiality agreements;

  • disclose legally or commercially protected information;

  • violate institutional or contractual obligations; or

  • create significant ethical, security, or biosecurity risks.

Where appropriate, data should be anonymized or de-identified before sharing.

If data cannot be shared, authors should explain the reason in the Data Availability Statement without revealing confidential or sensitive information.

5. Data Citation

Datasets that are publicly available and used in a manuscript should be cited appropriately.

Data citations should, whenever available, include:

  • author(s) or creator(s);

  • year;

  • dataset title;

  • repository or publisher;

  • version, where applicable; and

  • persistent identifier such as a DOI.

Previously published or third-party datasets should be cited both in the manuscript text and in the reference list where appropriate.

Authors are responsible for ensuring that they have the right to use and cite third-party datasets.

6. Data, Code, and Computational Reproducibility

For studies involving computational analyses, machine learning, artificial intelligence, statistical modeling, or other reproducible computational workflows, authors are encouraged to provide sufficient information to allow readers to understand and, where reasonably possible, reproduce the analysis.

Depending on the nature of the study, this may include:

  • analysis code;

  • software version;

  • algorithms;

  • model architecture;

  • model parameters and hyperparameters;

  • preprocessing procedures;

  • randomization procedures or random seeds where scientifically relevant;

  • training, validation, and test-set procedures;

  • prompts or prompt-design procedures where generative AI is part of the research methodology; and

  • other methodological information necessary for interpretation or reproducibility.

The extent of disclosure should be appropriate to the research design and must comply with ethical, legal, privacy, intellectual-property, and security requirements.

7. Data Integrity and Verification

Authors are responsible for the accuracy, authenticity, integrity, and appropriate documentation of the research data supporting their manuscript.

Research data must not be fabricated, falsified, selectively manipulated, or misleadingly presented.

Editors or reviewers may request access to relevant underlying data, code, documentation, or methodological information when necessary to:

  • assess the reliability of reported findings;

  • clarify methodological issues;

  • investigate potential inconsistencies; or

  • evaluate concerns relating to research or publication integrity.

Failure to provide requested information without a reasonable explanation may affect the editorial evaluation of the manuscript.

8. Data Retention

Authors are expected to retain the research data and documentation underlying their published work for an appropriate period in accordance with applicable institutional, funder, disciplinary, ethical, and legal requirements.

Where institutional or funding-body requirements specify a particular retention period, authors should comply with those requirements.

9. Ethical and Legal Responsibilities

Data sharing does not remove the authors' responsibilities regarding:

  • ethical approval;

  • informed consent;

  • protection of personal data;

  • confidentiality;

  • intellectual property;

  • copyright;

  • contractual obligations; and

  • applicable national and international regulations.

Authors must ensure that data sharing is consistent with the consent obtained from participants and the conditions approved by the relevant ethics committee, where applicable.

10. Post-Publication Data Concerns

If concerns arise after publication regarding the integrity, availability, provenance, or reliability of research data, YZIB may request clarification or supporting documentation from the authors.

Where necessary, the journal may take appropriate editorial action in accordance with its publication ethics, correction, retraction, and research-integrity policies.

11. Policy Updates

Research-data practices and international standards continue to evolve. YZIB reserves the right to review and update this policy when necessary to reflect developments in research integrity, open science, data protection, and scholarly publishing.